Q-omics provides the consensus-scored HPS3 profile across patient tissues and cancer cell-line models. HPS3 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, HPS3 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, HPS3 RNA expression shows 19,690 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight LIHC, HNSC, and ACC as cancer lineages where HPS3 shows reproducible signals across survival, tumor–normal expression, and patient cross-omics analyses.
Every result is evaluated using two consensus scores. Sampling consensus measures how consistently a finding is reproduced within a cancer lineage across different conditions. Lineage consensus measures how broadly the result is shared across cancer types, distinguishing pan-cancer signals from lineage-specific patterns.
Premium analyses for HPS3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HPS3 survival associations across molecular data types. HPS3 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (6) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HPS3 RNA expression–survival associations across cancer types. High HPS3 expression shows unfavorable associations in LIHC, KICH, LGG, UCEC, ACC and MESO. The LIHC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify LIHC as the clearest survival context for HPS3 RNA expression.
This table summarizes HPS3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for HPS3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HPS3 shows higher tumor expression in HNSC, KIRC, LUAD, LIHC, BLCA and STAD. The HNSC box plot shows higher HPS3 RNA expression in tumor versus normal tissue (log2 FC = +1.363, t-test p < 0.001).
This table shows molecular features associated with HPS3 in patient tissues and cancer cell lines. In patient samples, HPS3 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, HPS3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in LIVER and BLOOD_Leukemia.
